Proactively selection of input variables based on information gain factors for deep learning models in short-term solar irradiance forecasting

Y Chen, M Bai, Y Zhang, J Liu, D Yu - Energy, 2023 - Elsevier
As the proportion of solar power generation increases, accurate solar irradiance forecast
used to connect solar power to the grid has become crucial. Multi-parameter prediction is …

A novel scoring function based on family transfer entropy for Bayesian networks learning and its application to industrial alarm systems

QQ Meng, QX Zhu, HH Gao, YL He, Y Xu - Journal of Process Control, 2019 - Elsevier
Bayesian network (BN) is a powerful reasoning and knowledge expression tool combining
the graph theory and the probability theory. Establishing an accurate Bayesian network for …

Scale-reasoning based risk propagation analysis: An application to fluid catalytic cracking unit

S Cai, L Zhang, J Hu - Process Safety and Environmental Protection, 2018 - Elsevier
When a disturbance occurs in a complex large-scale system, it may affect downstream
equipment and several other process variables to evolve into a larger risk. The connectivity …

Interaction analysis–based information modeling of complex electromechanical systems in the processing industry

R Wang, J Gao, Z Gao, X Gao… - Proceedings of the …, 2017 - journals.sagepub.com
Information modeling for complex electromechanical systems in the processing industry is
the foundation for system vulnerability analysis, failure propagation mechanism, and fault …

Reconstruction of process topology using historical data and process models

A Ongalbayeva - 2016 - open.library.ubc.ca
Modern process industries are large and complex. Their units are highly interconnected with
each other. If there is an abnormal situation in the process, the faults might propagate from …